• Title/Summary/Keyword: technology performance

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Current research trends in HACCP principles (HACCP의 연구동향)

  • Hwang, Tae-Young;Lee, Sun-Yong;Yoo, Jae-Weon;Kim, Dong-Ju;Lee, Je-Myung;Go, Ji-Hun;Kim, Myung-Ho
    • Food Science and Industry
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    • v.54 no.2
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    • pp.93-101
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    • 2021
  • Hazard Analysis Critical Control Point (HACCP) systems were developed to ensure a high level of food safety and reduced risk of foodborne illness. This paper focuses on significant issues associated with the implementation of HACCP; it provides an overview on recent literature. The structure of the paper follows six groupings of issues in the international literature of HACCP: (1) comparative studies and unification plan between HACCP and other food safety regulations; (2) verification of the HACCP system's effectiveness in improving food safety; (3) establishment of critical control point (CCP) for various foods HACCP model development; (4) expansion of HACCP application in the various fields and small businesses;(5) the impacts of HACCP on consumer's preferences and firms' financial performance in food industry; (6) HACCP and technological changes. The paper concludes with some suggestions for the future research in order to promote safe food supply chain for global customers.

Quantitative analysis of glycerol concentration in red wine using Fourier transform infrared spectroscopy and chemometrics analysis

  • Joshi, Rahul;Joshi, Ritu;Amanah, Hanim Zuhrotul;Faqeerzada, Mohammad Akbar;Jayapal, Praveen Kumar;Kim, Geonwoo;Baek, Insuck;Park, Eun-Sung;Masithoh, Rudiati Evi;Cho, Byoung-Kwan
    • Korean Journal of Agricultural Science
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    • v.48 no.2
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    • pp.299-310
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    • 2021
  • Glycerol is a non-volatile compound with no aromatic properties that contributes significantly to the quality of wine by providing sweetness and richness of taste. In addition, it is also the third most significant byproduct of alcoholic fermentation in terms of quantity after ethanol and carbon dioxide. In this study, Fourier transform infrared (FT-IR) spectroscopy was employed as a fast non-destructive method in conjugation with multivariate regression analysis to build a model for the quantitative analysis of glycerol concentration in wine samples. The samples were prepared by using three varieties of red wine samples (i.e., Shiraz, Merlot, and Barbaresco) that were adulterated with glycerol in concentration ranges from 0.1 to 15% (v·v-1), and subjected to analysis together with pure wine samples. A net analyte signal (NAS)-based methodology, called hybrid linear analysis in the literature (HLA/GO), was applied for predicting glycerol concentrations in the collected FT-IR spectral data. Calibration and validation sets were designed to evaluate the performance of the multivariate method. The obtained results exhibited a high coefficient of determination (R2) of 0.987 and a low root mean square error (RMSE) of 0.563% for the calibration set, and a R2 of 0.984 and a RMSE of 0.626% for the validation set. Further, the model was validated in terms of sensitivity, selectivity, and limits of detection and quantification, and the results confirmed that this model can be used in most applications, as well as for quality assurance.

Development of the Shortest Path Algorithm for Multiple Waypoints Based on Clustering for Automatic Book Management in Libraries (도서관의 자동 도서 관리를 위한 군집화 기반 다중경유지의 최단 경로 알고리즘 개발)

  • Kang, Hyo Jung;Jeon, Eun Joo;Park, Chan Jung
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.541-551
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    • 2021
  • Among the numerous duties of a librarian in a library, the work of arranging books is a job that the librarian has to do one by one. Thus, the cost of labor and time is large. In order to solve this problem, the interest in book-arranging robots based on artificial intelligence has recently increased. In this paper, we propose the K-ACO algorithm, which is the shortest path algorithm for multi-stops that can be applied to the library book arrangement robots. The proposed K-ACO algorithm assumes multiple robots rather than one robot. In addition, the K-ACO improves the ANT algorithm to create K clusters and provides the shortest path for each cluster. In this paper, the performance analysis of the proposed algorithm was carried out from the perspective of book arrangement time. The proposed algorithm, the K-ACO algorithm, was applied to a university library and compared with the current book arrangement algorithm. Through the simulation, we found that the proposed algorithm can allocate fairly, without biasing the work of arranging books, and ultimately significantly reduce the time to complete the entire work. Through the results of this study, we expect to improve quality services in the library by reducing the labor and time costs required for arranging books.

Statistical Analysis of Extreme Values of Financial Ratios (재무비율의 극단치에 대한 통계적 분석)

  • Joo, Jihwan
    • Knowledge Management Research
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    • v.22 no.2
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    • pp.247-268
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    • 2021
  • Investors mainly use PER and PBR among financial ratios for valuation and investment decision-making. I conduct an analysis of two basic financial ratios from a statistical perspective. Financial ratios contain key accounting numbers which reflect firm fundamentals and are useful for valuation or risk analysis such as enterprise credit evaluation and default prediction. The distribution of financial data tends to be extremely heavy-tailed, and PER and PBR show exceedingly high level of kurtosis and their extreme cases often contain significant information on financial risk. In this respect, Extreme Value Theory is required to fit its right tail more precisely. I introduce not only GPD but exGPD. GPD is conventionally preferred model in Extreme Value Theory and exGPD is log-transformed distribution of GPD. exGPD has recently proposed as an alternative of GPD(Lee and Kim, 2019). First, I conduct a simulation for comparing performances of the two distributions using the goodness of fit measures and the estimation of 90-99% percentiles. I also conduct an empirical analysis of Information Technology firms in Korea. Finally, exGPD shows better performance especially for PBR, suggesting that exGPD could be an alternative for GPD for the analysis of financial ratios.

Comparison of the Priority of Required Capabilities of the Warrior Platform by the Types of Military Unit through AHP Analysis (AHP 분석을 통한 부대 임무유형별 워리어플랫폼 요구능력 우선순위 비교)

  • Kim, Wukki;Shin, Kyuyong;Jo, Seongsik;Baek, Seungho;Kim, Yongchul
    • Journal of Convergence for Information Technology
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    • v.11 no.6
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    • pp.262-269
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    • 2021
  • The Ministry of National Defense is re-establishing the role of the Army in accordance with the defense reform and is promoting the Warrior Platform, a next-generation individual combat system. The Warrior Platform project is divided into three stages and is being promoted. In the first stage, the quality and performance of individual items are improved, in the second stage, items between system development are integrated, and in the third stage, the combat capability is maximized by developing an integrated unit weapon system. In this paper, detailed sub-items for the five essential required competencies (survival, lethality, mobility, sustainability, Communication) that are considered for building an effective warrior platform are presented. We also present a plan that can be used to prepare a specific master plan for the Army's Warrior Platform project by using Analytic Hierarchy Process(AHP) and selecting the priority of the five required capabilities and detailed sub-items for different unit types. As a result of analyzing the priorities of the four types of units with different mission types, we find that there are differences for each unit. These results are expected to be used as useful reference materials for setting the future direction for the development of warrior platform.

Development of Artificial Intelligence Model for Predicting Citrus Sugar Content based on Meteorological Data (기상 데이터 기반 감귤 당도 예측 인공지능 모델 개발)

  • Seo, Dongmin
    • The Journal of the Korea Contents Association
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    • v.21 no.6
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    • pp.35-43
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    • 2021
  • Citrus quality is generally determined by its sugar content and acidity. In particular, sugar content is a very important factor because it determines the taste of citrus. Currently, the most commonly used method of measuring citrus sugar content in farms is a portable juiced sugar meter and a non-destructive sugar meter. This method can be easily measured by individuals, but the accuracy of the sugar content is inferior to that of the citrus NongHyup official machine. In particular, there is an error difference of 0.5 Brix or more, which is still insufficient for use in the field. Therefore, in this paper, we propose an AI model that predicts the citrus sugar content of unmeasured days within the error range of 0.5 Brix or less based on the previously collected citrus sugar content and meteorological data (average temperature, humidity, rainfall, solar radiation, and average wind speed). In addition, it was confirmed that the prediction model proposed through performance evaluation had an mean absolute error of 0.1154 for Seongsan area and 0.1983 for the Hawon area in Jeju Island. Lastly, the proposed model supports an error difference of less than 0.5 Brix and is a technology that supports predictive measurement, so it is expected that its usability will be highly progressive.

Hybrid Machine Learning Model for Predicting the Direction of KOSPI Securities (코스피 방향 예측을 위한 하이브리드 머신러닝 모델)

  • Hwang, Heesoo
    • Journal of the Korea Convergence Society
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    • v.12 no.6
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    • pp.9-16
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    • 2021
  • In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

Structural Characteristics Analysis of Steel Box Girder Bridge being stressed the PS Steel Wires at the Upper Slab of the Intermediate Support (지점부 상부슬래브에 PS강선 긴장된 강 박스거더교의 구조적 특성 분석)

  • Cha, Tae-Gweon;Jang, Il-Young
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.25 no.2
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    • pp.1-7
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    • 2021
  • The concrete deck slab at the continuous span support of the steel box girder bridge is a structure that is combined with the upper flange. It is a structure that can cause tension cracks in the deck slab at the support causing problems such as durability degradation in long span bridges. This is because the tensile stress in the longitudinal direction of the slab exceeds the design tensile strength due to the effects of dead load and live load when applying a long span. Accordingly, it is necessary to control tensile cracking by adding a reinforcing bar in the axial direction to the slab at the support and to introduce additional compressive stress. To solve this problem, a structural system of a steel box girder bridge was proposed that introduces compressive stress as PS steel wire tension in the tensile stress section of the upper slab in the continuous support. The resulting structural performance was compared and verified through the finite element analysis and the steel wire tension test of the actual specimen. By introducing compressive stress that can control the tensile stress and cracking of the slab generated in the negative moment through the tension of the PS steel wire, it is possible to improve structural safety and strengthen durability compared to the existing steel box girder bridge.

Assessment Module Formulation for the Trapped-Oil Recovery Operations from Sunken Vessels (침몰선 잔존유 회수작업 평가모듈 개발에 관한 연구)

  • Kang, Kwang-gu;Lee, Eun-bang
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.1
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    • pp.88-96
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    • 2021
  • When oil tankers, large passenger ships and cargo ships sink under the sea owing to various maritime accidents, the residual cargo oil or fuel oil in the such vessels could pose direct risk to factor for the marine environment and it require safe and rapid removal. Although domestic and foreign salvage companies are adopting various recovery methods and technologies with customizations according to each site during recovery operations studies on reasonable assessment modules for the operation process are relatively insufficient. In this study, the data from trapped-oil recovery operations performed at different site conditions were collected and analyzed in order to designed an operation assessment module, define the operational process steps in terms of preparation, implementation and completion, and derive key factors for each detailed process. Subsequently, the module was designed in such a way as to construct performance indicators to assess these key factors. In order to exclude subjective opinions from the assessment as much as possible, the assessment each item was constructed with indicators based on data that could be evaluated quantitatively and its usefulness was verified by applying the module to the trapped-oil recovery operation cases. We expect this the method and the technology assessment module for the trapped-oil recovery operation on sunken vessels will help to verify the adequacy of the trapped-oil recovery such operation before or after. Furthermore, it is expected that the continuous accumulation of assessment data and feedback from past or future operation cases will contribute toward enhancing the overall safety, efficiency and field applicability of trapped-oil recovery operation.

Evaluating Chloride Absorption of Reinforced Concrete Structures with Crack Widths (균열 폭에 따른 콘크리트 구조물에서의 염화물 흡수 평가)

  • Kim, Kun-Soo;Park, Ki-Tae;Kim, Jaehwan
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.24 no.6
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    • pp.10-16
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    • 2020
  • Deterioration of reinforced concrete structure caused by chloride ingress is the main issue and regrading this, many studies have been investigated with both experiments and computational modelling. In addition to chloride diffusion, chloride sorption should be considered as a chloride transport mechanism in concrete structure and cracks formed in concrete structures are the main variable to evaluate the performance of the structures. In this study, after making two types of cracks width (0.1 and 0.3 mm) in reinforced concretes, chloride absorption tests were performed. Weight change and colour change using 0.1 AgNO3 solution from the samples were performed to measure chloride ingress. Image processing was also carried out to quantify range of colour change in carck face. From the result, it were confirmed that the amount of chloride absorption increases with exposure time and increasing crack width, and chlorides reached at steel depth within 1 hour. It would be possible that chloride can move through interface bewteen steel and concrete, thereby further study regarding this is required.